Triple

T19291457
Position Surface form Disambiguated ID Type / Status
Subject Biougra E482450 entity
Predicate partOf P40 FINISHED
Object Souss plain NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Souss plain | Statement: [Biougra, partOf, Souss plain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Souss plain
Context triple: [Biougra, partOf, Souss plain]
  • A. Souss Tachelhit
    Souss Tachelhit is a major regional variety of the Tachelhit Berber language spoken primarily in Morocco’s Souss region.
  • B. Souss-Massa chosen
    Souss-Massa is an administrative region in southwestern Morocco known for its Atlantic coastline, agricultural production, and proximity to the Anti-Atlas mountains.
  • C. Bassin Agdal
    Bassin Agdal is a historic royal water reservoir located within the Agdal Gardens of Marrakech, Morocco.
  • D. Toshka
    Toshka is a region in southern Egypt best known for the Toshka Lakes and large-scale desert reclamation and irrigation projects near Lake Nasser.
  • E. Tanezrouft region
    The Tanezrouft region is an extremely arid, sparsely inhabited desert area in the central Sahara, known as one of the hottest and driest places on Earth.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8e8cf61b0819096fe3e4107827c4e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fc05c9dc8190846b279f82ae0fa3 completed April 20, 2026, 10:12 a.m.
Created at: April 10, 2026, 1:31 p.m.